Joint transform coding of multiple color components

ABSTRACT

There is included a method and apparatus comprising computer code configured to cause a processor or processors to perform receiving video data in an AOMedia Video 1 (AV1) format comprising data of at least two chroma prediction-residual signal blocks, a transformation between at least one signal block, having a size less than or equal to a combination of the chroma prediction-residual signal blocks, and the chroma prediction-residual signal blocks, and decoding the video data based on an output of the transformation comprising the at least one signal block having the size less than or equal to the combination of the chroma prediction-residual blocks.

CROSS-REFERENCES TO RELATED APPLICATIONS/PRIORITY CLAIM

The present application claims priority to provisional application US63/000,109 filed on Mar. 26, 2020 which is hereby expressly incorporatedby reference, in its entirety, into the present application.

FIELD

This disclosure relates generally to field of data processing, and moreparticularly to video encoding and/or decoding.

BACKGROUND

AOMedia Video 1 (AV1) is an open video coding format designed for videotransmissions over the Internet. It was developed as a successor to VP9by the Alliance for Open Media (AOMedia), a consortium founded in 2015that includes semiconductor firms, video on demand providers, videocontent producers, software development companies and web browservendors. In AV1, there is a total 56 directional angles, of which 8 arenominal angles and the remainder are specified as a delta from thenominal angles.

Many of the components of the AV1 project were sourced from previousresearch efforts by Alliance members. Individual contributors startedexperimental technology platforms years before: Xiph's/Mozilla's Daalaalready published code in 2010, Google's experimental VP9 evolutionproject VP10 was announced on 12 Sep. 2014, and Cisco's Thor waspublished on 11 Aug. 2015. Building on the codebase of VP9, AV1incorporates additional techniques, several of which were developed inthese experimental formats. The first version 0.1.0 of the AV1 referencecodec was published on 7 Apr. 2016. The Alliance announced the releaseof the AV1 bitstream specification on 28 Mar. 2018, along with areference, software-based encoder and decoder. On 25 Jun. 2018, avalidated version 1.0.0 of the specification was released. On 8 Jan.2019 a validated version 1.0.0 with Errata 1 of the specification wasreleased. The AV1 bitstream specification includes a reference videocodec.

ITU-T VCEG (Q6/16) and ISO/IEC MPEG (JTC 1/SC 29/WG 11) published theH.265/HEVC (High Efficiency Video Coding) standard in 2013 (version 1)2014 (version 2) 2015 (version 3) and 2016 (version 4). Since then theyhave been studying the potential need for standardization of futurevideo coding technology which could significantly outperform HEVC incompression capability. In October 2017, they issued the Joint Call forProposals on Video Compression with Capability beyond HEVC (CfP). ByFeb. 15, 2018, total 22 CfP responses on standard dynamic range (SDR),12 CfP responses on high dynamic range (HDR), and 12 CfP responses on360 video categories were submitted, respectively. In April 2018, allreceived CfP responses were evaluated in the 122 MPEG/10th JVET (JointVideo Exploration Team—Joint Video Expert Team) meeting. With carefulevaluation, JVET formally launched the standardization ofnext-generation video coding beyond HEVC, i.e., the so-called VersatileVideo Coding (VVC).

In AV1, prediction residual signals are generated for chroma channels,e.g., Cb and Cr, by various means and applied for in intra and intercoding scenarios, respectively. Since same sets of prediction methodsare applied to Cb and Cr channels in most cases, the resulting residualsignals from different chroma channels tend to be correlated in acertain way that can be categorized. Note that AV1 does not have codingtools to remove such redundancy for better compression efficiency. Onthe other hand, even though the current VVC design does provide one wayof leveraging on such tendencies, it is limited in the sense that itutilizes the correlation only between the two co-located chroma samples.

SUMMARY

This disclosure presents a set of advanced video coding technologies.More specifically, a transform scheme for joint coding of residuals frommultiple color components, e.g., residuals from two chroma components,is disclosed.

There is included a method and apparatus comprising memory configured tostore computer program code and a processor or processors configured toaccess the computer program code and operate as instructed by thecomputer program code. The computer program includes receiving codeconfigured to cause the at least one processor to receive video data inan AOMedia Video 1 (AV1) format comprising data of at least two chromaprediction-residual signal blocks, performing code configured to causethe at least one processor to perform a transformation between at leastone signal block, having a size less than or equal to a combination ofthe chroma prediction-residual signal blocks, and the chromaprediction-residual signal blocks, and decoding code configured to causethe at least one processor to decode the video data based on an outputof the transformation comprising the at least one signal block havingthe size less than or equal to the combination of the chromaprediction-residual blocks.

According to exemplary embodiments, the chroma prediction-residualsignal blocks comprise an N1×N2 Cb residual block and an N1×N2 Crresidual block.

According to exemplary embodiments, the transformation comprisesdequantizing signaled indices of coefficients of the at least one signalblock, having the size less than or equal to the combination of thechroma prediction-residual signal blocks, and transforming thedequantized signaled indices by a 2×N1×N2 by L×M matrix, and 2×N1×N2 isa size of the combination of the chroma prediction-residual blocks, andL×M is the size less than or equal to the combination of the chromaprediction residual blocs.

According to exemplary embodiments, a result of transforming thedequantized signaled indices by a 2×N1×N2 by L×M matrix comprises areconstructed 2×N1×N2 vector, and decoding the video data comprisesreconstructing the N1×N2 Cb residual block and the N1×N2 Cr residualblock from the reconstructed 2×N1×N2 vector.

According to exemplary embodiments, the at least one signal blockcomprises an interleaving of the at least two chroma prediction-residualsignal blocks.

According to exemplary embodiments, the at least one signal blockcomprises a 2×N1×N2 three-dimensional (3-D) cubic.

According to exemplary embodiments, the transformation comprises anN1-point 1-D transform, on each of N1×1 vectors along an x-axis of the3-D cubic, an N2-point 1-D transform, on each of N2×1 vectors along ay-axis of the 3-D cubic, and a 2-point transform on each of 2×1 vectorsalong a z-axis of the 3-D cubic.

According to exemplary embodiments, the transformation comprises atwo-point 1-D transform, on each of 2×1 vectors along a z-axis of the3-D cubic, and an N1×N2 transform on an x-y plane of the 3-D cubic.

According to exemplary embodiments, performing the transformationcomprises performing a primary transformation and a secondarytransformation.

According to exemplary embodiments, at least one of the primarytransformation and the secondary transformation comprises settingcoefficients to zero in response to determining a predeterminedcondition in which a value of a coordinate associated with a coefficientof at least one of the chroma prediction-residual signal blocks isgreater than or equal a threshold value.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects, features and advantages will become apparentfrom the following detailed description of illustrative embodiments,which is to be read in connection with the accompanying drawings. Thevarious features of the drawings are not to scale as the illustrationsare for clarity in facilitating the understanding of one skilled in theart in conjunction with the detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2 is a diagram of the nominal angles of AV1, according to at leastone embodiment;

FIG. 3 is an operational flowchart illustrating the steps carried out bya program that codes video data, according to at least one embodiment;

FIG. 4 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 5 is a block diagram of an illustrative cloud computing environmentincluding the computer system depicted in FIG. 1, according to at leastone embodiment; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, according to at least one embodiment.

FIG. 7 is a block diagram of features with respect to non-directionalsmooth intra predictors in AVI according to exemplary embodiments.

FIG. 8 is a block diagram of features with respect to recursive intrafiltering modes according to exemplary embodiments.

FIG. 9 is a block diagram of features with respect to a multi-layerreference frame structure according to exemplary embodiments.

FIG. 10 is a block diagram of features with respect to candidate motionvector list building according to exemplary embodiments.

FIG. 11 is a line diagram of features with respect to motion-fieldestimation according to exemplary embodiments.

FIG. 12 is a block diagram of features with respect to overlappingregions for overlapped block motion compensation (OMBC) according toexemplary embodiments.

FIG. 13 is a block diagram of features with respect to warped motioncompensation according to exemplary embodiments.

FIG. 14 is a block diagram of features with respect to advanced compoundprediction according to exemplary embodiments.

FIG. 15 is a flow diagram of features according to exemplaryembodiments.

FIG. 16 is a spatial diagram of features with respect to residuals puttogether as a 3D cube according to exemplary embodiments.

FIG. 17 is a block diagram of features with respect to a systemaccording to exemplary embodiments.

FIG. 18 is a block diagram of features with respect to a decoderaccording to exemplary embodiments.

FIG. 19 is a block diagram of features with respect to an encoderaccording to exemplary embodiments.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. Those structures and methods may, however, beembodied in many different forms and should not be construed as limitedto the exemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope to those skilled in the art. Inthe description, details of well-known features and techniques may beomitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments relate generally to the field of data processing, and moreparticularly to video encoding and decoding. The following describedexemplary embodiments provide a system, method and computer program to,among other things, encode and/or decode video data using delta anglevalues derived from nominal angle values. Therefore, some embodimentshave the capacity to improve the field of computing by not requiringevery delta angle to be signaled and allowing for on-the-flycalculations of delta angle values.

As previously described, AOMedia Video 1 (AV1) is an open video codingformat designed for video transmissions over the Internet. It wasdeveloped as a successor to VP9 by the Alliance for Open Media(AOMedia), a consortium founded in 2015 that includes semiconductorfirms, video on demand providers, video content producers, softwaredevelopment companies and web browser vendors. In AV1, there is a total56 directional angles, of which 8 are nominal angles and the remainderare specified as a delta from the nominal angles. However, both thenominal angles and the delta angles of all directional modes aresignalled for chroma component, regardless of the collocated lumaprediction modes. Additionally, delta angles are allowed for both lumaand chroma intra prediction modes, but the correlation of the deltaangles between luma and chroma component is not used. It may beadvantageous, therefore, to derive delta angle values for the chromacomponent based on nominal angles from the luma component instead ofsignaling all 56 angle values.

Aspects are described herein with reference to flowchart illustrationsand/or block diagrams of methods, apparatus (systems), and computerreadable media according to the various embodiments. It will beunderstood that each block of the flowchart illustrations and/or blockdiagrams, and combinations of blocks in the flowchart illustrationsand/or block diagrams, can be implemented by computer readable programinstructions.

Referring now to FIG. 1, a functional block diagram of a networkedcomputer environment illustrating a video coding system 100 (hereinafter“system”) for encoding and/or decoding video data using delta anglesderived from nominal angles. It should be appreciated that FIG. 1provides only an illustration of one implementation and does not implyany limitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironments may be made based on design and implementationrequirements.

The system 100 may include a computer 102 and a server computer 114. Thecomputer 102 may communicate with the server computer 114 via acommunication network 110 (hereinafter “network”). The computer 102 mayinclude a processor 104 and a software program 108 that is stored on adata storage device 106 and is enabled to interface with a user andcommunicate with the server computer 114. As will be discussed belowwith reference to FIG. 4 the computer 102 may include internalcomponents 800A and external components 900A, respectively, and theserver computer 114 may include internal components 800B and externalcomponents 900B, respectively. The computer 102 may be, for example, amobile device, a telephone, a personal digital assistant, a netbook, alaptop computer, a tablet computer, a desktop computer, or any type ofcomputing devices capable of running a program, accessing a network, andaccessing a database.

The server computer 114 may also operate in a cloud computing servicemodel, such as Software as a Service (SaaS), Platform as a Service(PaaS), or Infrastructure as a Service (IaaS), as discussed below withrespect to FIGS. 6 and 7. The server computer 114 may also be located ina cloud computing deployment model, such as a private cloud, communitycloud, public cloud, or hybrid cloud.

The server computer 114, which may be used for encoding video data isenabled to run a Video Encoding Program 116 (hereinafter “program”) thatmay interact with a database 112. The Video Encoding Program method isexplained in more detail below with respect to FIG. 3. In oneembodiment, the computer 102 may operate as an input device including auser interface while the program 116 may run primarily on servercomputer 114. In an alternative embodiment, the program 116 may runprimarily on one or more computers 102 while the server computer 114 maybe used for processing and storage of data used by the program 116. Itshould be noted that the program 116 may be a standalone program or maybe integrated into a larger video encoding program.

It should be noted, however, that processing for the program 116 may, insome instances be shared amongst the computers 102 and the servercomputers 114 in any ratio. In another embodiment, the program 116 mayoperate on more than one computer, server computer, or some combinationof computers and server computers, for example, a plurality of computers102 communicating across the network 110 with a single server computer114. In another embodiment, for example, the program 116 may operate ona plurality of server computers 114 communicating across the network 110with a plurality of client computers. Alternatively, the program mayoperate on a network server communicating across the network with aserver and a plurality of client computers.

The network 110 may include wired connections, wireless connections,fiber optic connections, or some combination thereof. In general, thenetwork 110 can be any combination of connections and protocols thatwill support communications between the computer 102 and the servercomputer 114. The network 110 may include various types of networks,such as, for example, a local area network (LAN), a wide area network(WAN) such as the Internet, a telecommunication network such as thePublic Switched Telephone Network (PSTN), a wireless network, a publicswitched network, a satellite network, a cellular network (e.g., a fifthgeneration (5G) network, a long-term evolution (LTE) network, a thirdgeneration (3G) network, a code division multiple access (CDMA) network,etc.), a public land mobile network (PLMN), a metropolitan area network(MAN), a private network, an ad hoc network, an intranet, a fiberoptic-based network, or the like, and/or a combination of these or othertypes of networks.

The number and arrangement of devices and networks shown in FIG. 1 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 1. Furthermore, two or more devices shown in FIG. 1 may beimplemented within a single device, or a single device shown in FIG. 1may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) of system100 may perform one or more functions described as being performed byanother set of devices of system 100.

Referring now to FIG. 2, a diagram 200 illustrating nominal angles ofAV1 is depicted. VP9 supports 8 directional modes corresponding toangles from 45 to 207 degrees. To exploit more varieties of spatialredundancy in directional textures, in AV1, directional intra modes areextended to an angle set with finer granularity. In AV1, there are 8nominal angles between 45 and 207 degrees that may include V_PRED,H_PRED, D45_PRED, D135_PRED, D113_PRED, D157_PRED, D203_PRED, andD67_PRED. For each nominal angle, there may be 7 finer angles, such thatAV1 may have 56 directional angles in total. The prediction angle may berepresented by a nominal intra angle plus an angle delta, which is −3˜3multiplies the step size of 3 degrees. The delta angles may not need tobe signaled by the chroma component but may instead by derived accordingto the corresponding luma intra prediction modes.

In AV1, 8 nominal modes together with 5 non-angular smooth modes arefirstly signaled, then if current mode is angular mode, an index isfurther signaled to indicate the angle delta to the correspondingnominal angle. To implement directional prediction modes in AV1 via ageneric way, all the 56 directional intra prediction mode in AV1 areimplemented with a unified directional predictor that projects eachpixel to a reference sub-pixel location and interpolates the referencepixel by a 2-tap bilinear filter.

In one or more embodiments, when the current chroma intra predictionmode is directional intra prediction mode and the nominal angle of thechroma intra prediction mode is equal to that of corresponding lumaintra prediction mode, then the delta angle of the chroma component maybe set equal to the delta angle of luma intra prediction mode.Otherwise, the delta angle of the chroma component may be set equal to0.

In one or more embodiments, the delta angle of the chroma component maybe set equal to the delta angle of the luma component, regardless ofwhether the nominal mode between luma and chroma is same or not.

In one or more embodiments, when the current chroma intra predictionmode is directional intra prediction mode and the nominal angle of thechroma intra prediction mode is equal to that of corresponding lumaintra prediction mode, then the delta angle of the chroma component maybe set equal to the delta angle of luma intra prediction mode.Otherwise, when the nominal angle of the chroma intra prediction mode isequal to the left/above neighboring modes of the corresponding lumablock, then the delta angle of the chroma component may be set equal tothat of left/above neighboring modes of the corresponding luma block.Otherwise, the delta angle of the chroma component may be set equal to0.

In one or more embodiments, when semi-decoupled partitioning is applied,there may be multiple luma blocks associated with one chroma block.Therefore, multiple sample positions may be pre-defined, and the deltaangles and nominal angles associated with these positions for predictingthe co-located luma block may be identified. One or more of theseidentified nominal angles and delta angles may be used to derive thedelta angles of current chroma block. In one example, the pre-definedsample positions may include the top-left and/or the center/middlesamples. In another example, the pre-defined sample positions mayinclude the four corner samples and the center/middle sample. In anotherexample, the delta angles that may be used most frequently among theidentified prediction modes may be used to derive the derive the deltaangles of the chroma component. In another example, the pre-definedsample positions may include two selected positions of the four cornersamples and one center/middle sample. In another example, thepre-defined sample positions may include three selected positions of thefour corner samples and one center/middle sample.

In one or more embodiments, when the current chroma intra predictionmode is directional intra prediction mode and the nominal angle of thechroma intra prediction mode is equal to that of corresponding lumaintra prediction mode, then the delta angle of the chroma component maybe set equal to the delta angle of luma intra prediction mode.Otherwise, when the nominal angle of the chroma intra prediction mode isequal to the left/above neighboring modes of current chroma block, thenthe delta angle of the chroma component may be set equal to that ofleft/above neighboring modes of current chroma block. Otherwise, thedelta angle of the chroma component may be set equal to 0.

The delta angle of the corresponding luma block may be used for theentropy coding of the delta angles of chroma intra prediction modes. Inone or embodiments, the delta angle of the co-located luma blocks may beused as the context for the entropy coding of the delta angles of thechroma component. In one or more embodiments, the delta angle of theneighboring chroma blocks is used as the context for the entropy codingof the delta angles of the chroma component. In one or embodiments,instead of signaling the delta angles of the current chroma block, theabsolute difference between delta angles of chroma blocks and thecorresponding luma blocks may be signaled for the entropy coding of thechroma intra prediction modes. In one or more embodiments, the aboveembodiments are applied only when the nominal mode between luma andchroma may be same or when the absolute difference of prediction anglesbetween these two modes is within a given threshold.

According to one or more embodiments, for entropy coding of the chromaintra prediction modes, a first flag may be signaled to indicate whetheror not the current mode is chroma-from-luma (CfL). If the first flag issignaled as a value indicating CfL is not being used, a second flag maybe signaled to indicate whether the current mode may be equal to thenominal mode of the corresponding luma block. If the current mode isequal to the nominal mode of the corresponding luma block, current modeis directional mode, and delta angles are allowed, then a third flag maybe signaled to indicate the index of the delta angles. Otherwise, thethird flag is signaled to indicate which of the remaining nominal modescurrent mode is. If the first flag is signaled as a value indicating CfLis not being used, the parameters of the CfL mode may be furthersignaled.

According to one or more embodiments, for entropy coding of the chromaintra prediction modes, the first flag may be signaled to indicatewhether current mode may be equal to the nominal mode of thecorresponding luma block or CfL mode. If the first flag is signaled as avalue indicating the current mode is equal to the nominal mode of thecorresponding luma block or CfL mode, the second flag may be signaled toindicate which of the two modes may be the current mode. If the currentmode is equal to the nominal mode of the corresponding luma block, thecurrent mode is directional mode, and delta angles are allowed, then theindex of the delta angles may be further signaled. If the current modeis CfL mode, the parameters of the CfL mode may be further signaled. Ifthe first flag is signaled as a value indicating the current mode is notequal to the nominal mode of the corresponding luma block or CfL mode,the second flag may be signaled to indicate which of the remainingnominal modes may be applied for the current chroma block.

In one or more embodiments, the first delta angle values may beentropy-coded based on using a delta angle of co-located luma blocks asa context in response to the nominal angle of the chroma component andthe nominal angle of the luma component being the same or close to eachother. The nominal angles may be close to each other when a differenceof the between the nominal angles is less than or equal to 2 degrees.The delta angle values may be entropy-coded based on using a delta angleof co-located luma blocks as a context or based on using a delta angleof neighboring chroma blocks as a context.

It may be appreciated that, in one or more embodiments, the delta anglesof luma and chroma blocks may use the separate contexts for entropycoding instead of sharing the same context among the delta angles of theluma and chroma blocks

Referring now to FIG. 3, an operational flowchart illustrating the stepsof a method 300 for encoding and/or decoding video data is depicted. Insome implementations, one or more process blocks of FIG. 3 may beperformed by the computer 102 (FIG. 1) and the server computer 114 (FIG.1). In some implementations, one or more process blocks of FIG. 3 may beperformed by another device or a group of devices separate from orincluding the computer 102 and the server computer 114.

At 302, the method 300 includes receiving video data including (1) achroma component having a first nominal angle and first delta angles and(2) a luma component having a second nominal angle and second deltaangles. The first delta angles are dependent on the second delta angles.

At 304, the method 300 includes signaling first delta angle values forthe first delta angles based on at least an intra prediction modeassociated with the luma component.

At 306, the method 300 includes encoding and/or decoding the video databased on the first delta angle values corresponding to the first deltaangles.

It may be appreciated that FIG. 3 provides only an illustration of oneimplementation and does not imply any limitations with regard to howdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

FIG. 4 is a block diagram 400 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment. It should be appreciated that FIG. 4 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

Computer 102 (FIG. 1) and server computer 114 (FIG. 1) may includerespective sets of internal components 800A,B and external components900A,B illustrated in FIG. 4. Each of the sets of internal components800 include one or more processors 820, one or more computer-readableRAMs 822 and one or more computer-readable ROMs 824 on one or more buses826, one or more operating systems 828, and one or morecomputer-readable tangible storage devices 830.

Processor 820 is implemented in hardware, firmware, or a combination ofhardware and software. Processor 820 is a central processing unit (CPU),a graphics processing unit (GPU), an accelerated processing unit (APU),a microprocessor, a microcontroller, a digital signal processor (DSP), afield-programmable gate array (FPGA), an application-specific integratedcircuit (ASIC), or another type of processing component. In someimplementations, processor 820 includes one or more processors capableof being programmed to perform a function. Bus 826 includes a componentthat permits communication among the internal components 800A,B.

The one or more operating systems 828, the software program 108 (FIG. 1)and the Video Encoding Program 116 (FIG. 1) on server computer 114(FIG. 1) are stored on one or more of the respective computer-readabletangible storage devices 830 for execution by one or more of therespective processors 820 via one or more of the respective RAMs 822(which typically include cache memory). In the embodiment illustrated inFIG. 4, each of the computer-readable tangible storage devices 830 is amagnetic disk storage device of an internal hard drive. Alternatively,each of the computer-readable tangible storage devices 830 is asemiconductor storage device such as ROM 824, EPROM, flash memory, anoptical disk, a magneto-optic disk, a solid state disk, a compact disc(CD), a digital versatile disc (DVD), a floppy disk, a cartridge, amagnetic tape, and/or another type of non-transitory computer-readabletangible storage device that can store a computer program and digitalinformation.

Each set of internal components 800A,B also includes a R/W drive orinterface 832 to read from and write to one or more portablecomputer-readable tangible storage devices 936 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the softwareprogram 108 (FIG. 1) and the Video Encoding Program 116 (FIG. 1) can bestored on one or more of the respective portable computer-readabletangible storage devices 936, read via the respective R/W drive orinterface 832 and loaded into the respective hard drive 830.

Each set of internal components 800A,B also includes network adapters orinterfaces 836 such as a TCP/IP adapter cards; wireless Wi-Fi interfacecards; or 3G, 4G, or 5G wireless interface cards or other wired orwireless communication links. The software program 108 (FIG. 1) and theVideo Encoding Program 116 (FIG. 1) on the server computer 114 (FIG. 1)can be downloaded to the computer 102 (FIG. 1) and server computer 114from an external computer via a network (for example, the Internet, alocal area network or other, wide area network) and respective networkadapters or interfaces 836. From the network adapters or interfaces 836,the software program 108 and the Video Encoding Program 116 on theserver computer 114 are loaded into the respective hard drive 830. Thenetwork may comprise copper wires, optical fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers.

Each of the sets of external components 900A,B can include a computerdisplay monitor 920, a keyboard 930, and a computer mouse 934. Externalcomponents 900A,B can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 800A,B also includes device drivers 840to interface to computer display monitor 920, keyboard 930 and computermouse 934. The device drivers 840, R/W drive or interface 832 andnetwork adapter or interface 836 comprise hardware and software (storedin storage device 830 and/or ROM 824).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,some embodiments are capable of being implemented in conjunction withany other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring to FIG. 5, illustrative cloud computing environment 500 isdepicted. As shown, cloud computing environment 500 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Cloud computingnodes 10 may communicate with one another. They may be grouped (notshown) physically or virtually, in one or more networks, such asPrivate, Community, Public, or Hybrid clouds as described hereinabove,or a combination thereof. This allows cloud computing environment 600 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 5 are intended to be illustrative only and that cloud computingnodes 10 and cloud computing environment 500 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring to FIG. 6, a set of functional abstraction layers 600 providedby cloud computing environment 500 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments are notlimited thereto. As depicted, the following layers and correspondingfunctions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and Video Encoding/Decoding 96. VideoEncoding/Decoding 96 may encode/decode video data using delta anglesderived from nominal angles.

FIG. 7 is a block diagram 700 of features with respect tonon-directional smooth intra predictors in AVI according to exemplaryembodiments. For example, in AV1, there are 5 non-directional smoothintra prediction modes, which are DC, PAETH, SMOOTH, SMOOTH_V, andSMOOTH_H. For DC prediction, the average of left and above neighboringsamples is used as the predictor of the block to be predicted. For PAETHpredictor, top, left and top-left reference samples are firstly fetched,and then the value which is closest to (top+left−topleft) is set as thepredictor for the pixel to be predicted. FIG. 7 illustrates thepositions of top, left, and top-left samples for one pixel in currentblock. For SMOOTH, SMOOTH_V, and SMOOTH_H modes, they predict the blockusing quadratic interpolation in the vertical or horizontal direction,or the average of both directions.

FIG. 8 is a block diagram 800 of features with respect to recursiveintra filtering modes according to exemplary embodiments. For example,to capture decaying spatial correlation with references on the edges,FILTER INTRA modes are designed for luma blocks. Five filter intra modesare pre-designed for AV1, each represented by a set of eight 7-tapfilters reflecting correlation between pixels in a 4×2 patch and 7neighbors adjacent to it. In other words, the weighting factors for7-tap filter are position dependent. Take an 8×8 block for example, itis split into 8 4×2 patches, which is shown in FIG. 8. These patches areindicated by B0, B1, B1, B3, B4, B5, B6, and B7 in FIG. 8. For eachpatch, its 7 neighbors, indicated by R0˜R7, are used to predict thepixels in current patch. For patch B0, all the neighbors are alreadyreconstructed. But for other patches, some of the neighbors are notreconstructed, then the predicted values of immediate neighbors are usedas the reference. For example, all the neighbors of patch B7 are notreconstructed, so the prediction samples of neighbors are used instead.

Chroma from Luma (CfL) is a chroma-only intra predictor that modelschroma pixels as a linear function of coincident reconstructed lumapixels. The CfL prediction is expressed as follows (equation 1 (“Eq.1”)):CfL(α)=α×L ^(AC) +DC  Eq. 1wherein L^(AC) denotes the AC contribution of luma component, a denotesthe parameter of the linear model, and DC denotes the DC contribution ofthe chroma component. To be specific, the reconstructed luma pixels aresubsampled into the chroma resolution, and then the average value issubtracted to form the AC contribution. To approximate chroma ACcomponent from the AC contribution, instead of requiring the decoder tocalculate the scaling parameters as in some prior art, AV1 CfLdetermines the parameter a based on the original chroma pixels andsignals them in the bitstream. This reduces decoder complexity andyields more precise predictions. As for the DC contribution of thechroma component, it is computed using intra DC mode, which issufficient for most chroma content and has mature fast implementations.

FIG. 9 is a block diagram 900 of features with respect to a multi-layerreference frame structure according to exemplary embodiments. Forexample, there may be extended reference frames such that in addition toVP9's 3 reference frames, i.e., LAST (nearest past), GOLDEN (distantpast), and ALTREF (temporally filtered future) frames, there are fourmore types of refence frames as follows:

-   -   LAST2 and LAST3: two near past frames    -   BWDREF, ALTREF2: two future frames    -   BWDREF is a look-ahead frame coded without temporal filtering        and more useful as a backward reference in a relatively short        distance.    -   ALTREF2 is an intermediate filtered future reference between        GOLDEN and ALTREF.

FIG. 10 is a block diagram 1000 of features with respect to candidatemotion vector list building according to exemplary embodiments. Forexample, with dynamic spatial and temporal motion vector referencing,AV1 incorporates motion-vector reference selection schemes toefficiently code motion vectors. It uses wider spatial neighbors thanits predecessor VP9 as well as motion-field estimation process to findtemporal motion-vector reference candidates.

FIG. 11 is a line diagram 1100 of features with respect to motion-fieldestimation according to exemplary embodiments. For example, themotion-field estimation process searches through the collocated 128×128area for all motion trajectories in 8×8 block resolution that pass each64×64 processing unit. For example, in FIG. 11, the motion vectorMV_(Ref2) is searched over following the said process and the projectedmotion vectors such as MV₀ and MV₁ are derived. Once all the candidatemotion-vectors are found, they are sorted, merged, and ranked to buildup to four final candidates. AV1 then signals the index of a selectedreference motion vector from the list and optionally codes the motionvector difference.

FIG. 12 is a block diagram 1200 of features with respect to overlappingregions for overlapped block motion compensation (OMBC) according toexemplary embodiments. For example, in order to decrease predictionerrors around block boundaries by combining predictions obtained fromadjacent motion vectors, AV1 progressively combines the block-basedprediction with secondary predictors from the top and left edges byapplying 1-D filters in vertical and horizontal directions,respectively. As an example, in FIG. 12, the shaded region of thepredicted block 0 will be predicted by recursively generating blendedprediction samples via a 1-D raised cosine filter. FIG. 12 shows theshaded regions to be predicted using a top-neighbor block 2 and theleft-neighbor block 4, respectively.

FIG. 13 is a block diagram 1300 of features with respect to warpedmotion compensation according to exemplary embodiments. For example, AV1introduces two affine prediction models, namely, a global and a localwarped motion compensation. The former signals frame-level affine modelbetween a frame and its reference while the latter handles varying localmotions implicitly with minimal overhead. Local motion parameters arederived at the block level using 2D motion vectors from the causalneighbors. This affine model is realized through a consecutivehorizontal and vertical shearing operation based upon an 8-tapinterpolation filter at 1/64 pixel precision. FIG. 13 shows a two-stepwarping process of horizontal-shearing followed by vertical one.

FIG. 14 is a block diagram 1400 of features with respect to advancedcompound prediction according to exemplary embodiments. For example,according to embodiments AV1 may allow for more versatile prediction ateach pixel position (i,j) as follows (definition 1 (“Def. 1”)):p(i,j)

m(i,j)P ₁(i,j)+(1−m(i,j))p ₂  Def. 1where p₁ and p₂ are two predictions and m(i,j) is a weighting factor in[0,1] looked up from predefined tables.

For a compound wedge prediction there is a predefined set of 16 possiblewedge partitions is provided in AV1 and its chosen wedge index issignaled. Its orientations include horizontal, vertical, and obliquewith slopes of ±2 or ±0.5 for both the square and rectangular blocks. Inorder to mitigate spurious artifacts, soft-cliff-shaped 2D wedge masksare employed.

For a difference-modulated masked prediction, according to embodimentsAV1 may allow for some regions of the prediction to come more heavilyfrom one prediction than the other. More specifically, the followingform of mask is used (“Def. 2”):m(i,j)

b+a|p ₁(i,j)−p ₂(i,j)|  Def. 2where b controls the influence of the first predictor and a ensuressmooth modulation.

For a frame distance based compound prediction, according to embodimentsAV1 may include a modified weighting scheme accounting for framedistance, which is defined as the absolute difference between timestampsof two frames. In order to take into consideration not only the temporaldistance, but also the reduction of quantization noise through averagingeffects of multiple references, AV1 employs a scheme based on the framedistance while giving slightly more weight toward the distant predictoras follows (“Def. 3” and “Def 4”):

$\begin{matrix}{p\overset{\bigtriangleup}{=}{{{round}\mspace{14mu}\left( {{w_{1}*p_{1}} + {w_{2}*p_{2}} + 8} \right)} ⪢ 4}} & {{Def}.\mspace{11mu} 3} \\{\left( {w_{1},\ w_{2}} \right)\overset{\bigtriangleup}{=}\left\{ \begin{matrix}{\left( {9,7} \right),} & {{{when}\mspace{14mu} 2d_{2}} < {3d_{1}}} \\{\left( {{11},5} \right),} & {{{when}\mspace{14mu} 2d_{2}} < {5d_{1}}} \\{\left( {{12},4} \right),} & {{{when}\mspace{14mu} 2d_{2}} < {7d_{1}}} \\{\left( {{13},3} \right),} & {{{when}\mspace{14mu} 2d_{2}} \geq {7d_{1}}}\end{matrix} \right.} & {{Def}.\mspace{11mu} 4}\end{matrix}$where p is the frame distance-based prediction and p₁ and p₂ areprediction values from two reference frames. The weights (w₁,w₂) aredetermined as above where d₁ and d₂ represent the frame distances of thecurrent frame from the two references.

For a compound inter-intra prediction, according to embodiments AV1 cancombine intra and inter predictions and four frequently used intra modesare supported for the intra-part. The masks associated with this modeare two types: (i) smooth wedge masks similar to the ones used forinter-inter modes, (ii) mode-dependent masks decaying along the primarydirection of the intra mode.

According to exemplary embodiments, for each transform unit, AV1coefficient coding starts with signaling a skip sign, and is followed bysignaling the transform kernel type and the end-of-block (eob) positionwhen the skip sign is zero. Then each coefficient value is mapped tomultiple level maps and the sign.

After the eob position is coded, the lower-level map and themiddle-level map are coded in reverse scan order, the former indicatingif the coefficient magnitude is between 0 and 2 while the latterindicating if the range is between 3 and 14. The next step codes, in theforward-scanning order, the sign of the efficient as well as theresidual value of the coefficient larger than 14 by Exp-Golomb code.

As for the use of context modeling, the lower-level map codingincorporates the transform size and directions as well as up to fiveneighboring coefficient information. On the other hand, the middle-levelmap coding follows a similar approach as with the lower-level amp codingexcept that the number of neighboring coefficients is down to two. TheExp-Golomb code for the residual level as well as the sign of ACcoefficient are coded without any context model while the sign of DCcoefficient is coded using its neighbor transform-unit's dc sign.

VVC Draft 6 supports a mode where the chroma residuals are codedjointly. The usage (activation) of a joint chroma coding mode isindicated by a TU-level flag tu_joint_cbcr_residual_flag and theselected mode is implicitly indicated by the chroma CBFs. The flagtu_joint_cbcr_residual_flag is present if either or both chroma CBFs fora TU are equal to 1. In the PPS and slice header, chroma QP offsetvalues are signalled for the joint chroma residual coding mode todifferentiate from the chroma QP offset values signalled for regularchroma residual coding mode. These chroma QP offset values are used toderive the chroma QP values for those blocks coded using the jointchroma residual coding mode. When a corresponding joint chroma codingmode (mode 2 in Table 1) is active in a TU, this chroma QP offset isadded to the applied luma-derived chroma QP during quantization anddecoding of that TU. For the other modes (modes 1 and 3 in Table 1), thechroma QPs are derived in the same way as for conventional Cb or Crblocks. The reconstruction process of the chroma residuals (resCb andresCr) from the transmitted transform blocks is depicted in Table 1.When this mode is activated, one single joint chroma residual block(resJointC[x][y] in Table 1) is signalled, and residual block for Cb(resCb) and residual block for Cr (resCr) are derived consideringinformation such as tu_cbf_cb, tu_cbf_cr, and CSign, which is a signvalue specified in the slice header.

The three joint chroma coding modes described above are only supportedin intra coded CU. In inter-coded CU, only mode 2 is supported. Hence,for inter coded CU, the syntax element tu_joint_cbcr_residual_flag isonly present if both chroma cbfs are 1. Table 1 below indicates areconstruction of chroma residuals, and the value CSign is a sign value(+1 or −1), which is specified in the slice header while resJointC[ ][ ]is the transmitted residual.

TABLE 1 tu_cbf_cb tu_cbf_cr reconstruction of Cb and Cr residuals mode 10 resCb[x][y] = resJointC[x][y] 1 resCr[x][y] = (CSign * resJointC[x][y]) >> 1 1 1 resCb[x][y] = resJointC[x][y] 2 resCr[x][y] = CSign *resJointC[x][y] 0 1 resCb[x][y] = (CSign * resJointC[x][y]) >> 1 3resCr[x][y] = resJointC[x][y]

The three joint chroma coding modes described above are only supportedin intra coded CU. In inter-coded CU, only mode 2 is supported. Hence,for inter coded CU, the syntax element tu_joint_cbcr_residual_flag isonly present if both chroma cbfs are 1. Table 1 below indicates areconstruction of chroma residuals, and the value CSign is a sign value(+1 or −1), which is specified in the slice header while resJointC[ ][ ]is the transmitted residual.

FIG. 15 is a flow diagram 1500 of features according to exemplaryembodiments.

FIG. 16 is a spatial diagram of features with respect to residuals puttogether as a 3D cube according to exemplary embodiments. The featuresof FIG. 16 and those described with respect to the other figures hereinmay be used separately or combined in any order. Further, each of themethods (or embodiments), encoder, and decoder may be implemented byprocessing circuitry (e.g., one or more processors or one or moreintegrated circuits). In one example, the one or more processors executea program that is stored in a non-transitory computer-readable medium.It is assumed that one or more N1×N2 Cb prediction residual block andits corresponding Cr prediction residual block are given as input atS151.

At S151, there is a transforming of two N1×N2 Cb and Crprediction-residual signal blocks into another one or more signal blocksof size M×L, where M×L is less than or equal to 2×N1×N2; however, one ormore modifications may be substituted or added at S151.

Improvements in a technical problem with respect to the above-describedcompression, for example, may be effected by transforms described hereinwhich remove redundancies between any of chroma prediction residuals andsimilar signals.

For example, according to exemplary embodiments, an N1×N2 Cb residualblock and its corresponding Cr residual block are put together as oneblock, and one transform is performed on this one block. There may be a2D-transform in which there is a vectorization of each input channelseparately by various scanning orders to achieve transform coefficientsof size L×M (herein “Type-I”). There may be a 2D-transform in whichthere is a vectorization of two input channels by interleaving inaddition to the scanning orders mentioned above (herein “Type-II”).

As more specific embodiments of Type-I and Type II, there may beseparate coding of two N1×N2 transform coefficient blocks according toexemplary embodiments with respect to one or more of:

-   -   (2×N1×N2) by (2×N1×N2) KLT (Karhunen-Loève Transform),    -   Reduced dimension KLT (RD-KLT),    -   Separable approximation of RD-KLT,    -   Givens/Permutation matrix decomposition, and    -   Combinations of Trigonometric transforms.

In one embodiment, when putting Cb and Cr together as one block at S151,the Cb and Cr residuals are vectorized separately following a zig-zag,raster, or diagonal scanning order, then concatenated to form a(2×N1×N2) by 1 vector. It is transformed by an (L×M) by (2×N1×N2) matrixto form a signal block of size (L×M) by 1. Its coefficients arequantized and the quantization indices are signaled. The decodingprocess dequantizes the indices and inverse-transforms them by a(2×N1×N2) by (L×M) matrix to obtain the reconstructed 2×N1×N2 vector,which can be reverse-scanned back to reconstructed Cb and Cr residualblocks.

In one embodiment, when putting Cb and Cr together as one block at S151,the Cb residual block and its corresponding Cr residual block arevectorized in an interleaved manner (i.e., one sample from Cb and thenext sample from Cr) with each sample taken from the residual blocksfollowing a zig-zag, raster, or diagonal scanning order to form a(2×N1×N2) by 1 vector. It is then transformed by an (L×M) by (2×N1×N2)matrix to form a transformed signal block of size (L×M) by 1. Itscoefficients are quantized and the quantization indices are signaled.The decoding process dequantizes the indices and inverse-transforms themby a (2×N1×N2) by (L×M) matrix to obtain the reconstructed 2×N1×N2vector, which can be reverse-scanned back to reconstructed Cb and Crresidual blocks.

In one embodiment, at S151 there is also a setting of L×M equal to2×N1×N2, and the output of transform is further split to two N1×N2blocks, which are separately further quantized, and decoded or entropycoded into the bitstream at S153.

In one embodiment, at S151 when L×M is equal to 2×N1×N2, the abovetransform matrix is of size (2×N1×N2) by (2×N1×N2) and can be determinedas the KLT (Karhunen-Loève Transform). Given the 2×N1×N2 by 1 inputvector signal X (assuming it was mean-removed to have zero-mean), the(2×N1×N2) by (2×N1×N2) covariance matrix R_(XX)

E[XX^(T)] satisfies the following equation (“Eq. 2”):R _(XX) I _(j)=λ_(j) I _(j)  Eq. 2where λ_(j) and I_(j) are j-th eigenvalue and the correspondingeigenvector of R_(XX).

The KLT matrix H has the above eigenvector as its rows and transforms Xinto Y as follows (“Eq. 3”):Y=HX  Eq. 3where H

[I₁ I₂ . . . I_(2×N1×N2)]^(T).

The elements of Y are uncorrelated and their variances are equal to theeigenvalues. In addition, H is an orthogonal transform so that the inputsignal vector X can be recovered as follows (“Eq. 4”):X=H ^(T) Y  Eq. 4

In one embodiment, at S151 the above (L×M) by (2×N1×N2) matrix can bedetermined by selecting only L×M eigenvectors corresponding to the L×Mlargest eigenvalues from (2×N1×N2) basis vectors of the KLT.

In one embodiment, at S151 the above determined (L×M) by (2×N1×N2) KLTcan be approximated by its separable approximations. As an example, thesaid KLT matrix H can be approximated by solving the followingoptimization problem (problem 1 (“Prob. 1”)):

$\begin{matrix}{\min\limits_{P,S}{{H - {P_{1}SP_{2}}}}_{F}} & {{Prob}.\mspace{11mu} 1}\end{matrix}$where S is a separable row/column matrix and P₁ and P₂ are permutationmatrices to be determined.

In one embodiment, at S151 the above (L×M) by (2×N1×N2) matrix can beconstructed as multiple stages of a Givens rotation matrix and/or apermutation matrix. As an example, the said KLT matrix H can beapproximated by solving the following optimization problem (“Prob. 2”):

$\begin{matrix}{\min\limits_{T}{{H - T}}_{F}} & {{Prob}.\mspace{11mu} 2}\end{matrix}$where T

Π_(k=1) ^(K)P_(k)G_(k)P_(k) ^(T) is a concatenation of multiple stages,each of which consists of a product of a Givens rotation matrix with apermutation matrix and its inverse.

In one embodiment, at S151 the above (L×M) by (2×N1×N2) matrix can beadaptively constructed from a set of DCT/DST transforms.

At S154, it may be determined whether an N1×N2 Cb residual block and itscorresponding Cr residual block are to be put together as one 2×N1×N2three-dimensional (3-D) cubic as shown in FIG. 16 with the cubic 1600,and if so then at S155 a 3-D transform is performed on this one cubic.

According to exemplary embodiments, there may be any of fully-separable3-D transforms and 1D+2D transforms used with these described features.

In one embodiment, at S155 this three-dimensional (3-D) transform can bedone separately along three axes. That is, an N1-point 1-D transform isperformed for each of the N1×1 vectors along x-axis, and an N2-point 1-Dtransform is performed for each of the N2×1 vectors along y-axis, andanother 2-point transform is performed for each of the 2×1 vectors alongthe z axis. The order of applications of these transforms can bearbitrary.

In one embodiment, at S155 this three-dimensional (3-D) transform can bedone separately along the z-axis while an arbitrary 2-D transform isperformed for the x-y planes. That is, a two-point 1-D transform isperformed for each of the 2×1 vectors along z-axis while an (N1×N2)transform is performed for the x-y planes.

At S156, it may be determined whether to further apply one or more ofthe transforms described with respect to S152 as a secondary transformwith the input being primary transform coefficients of chroma predictionresiduals.

For example, for each N1×N2 chroma residual, it only takes K1 transformcoefficients, and these two K1 coefficients are concatenated to form theinput to the Secondary transform as described with respect to S152 andspecific exemplary embodiments may include one or more of:

-   -   a restriction on the type of primary transform for which the        Secondary transform will be applied,    -   a zeroing-out of certain coefficients of the input to the        secondary transform, and    -   a separate coding of the primary-transform-only coefficients and        the rest.

If so from S156, then at S152 from S156 in one embodiment, the input ofthe forward secondary transform is the concatenation of the two sets offirst K1 (K⇐N1×N2) coefficients along the forward scanning order eachfrom transformed Cb residual and Cr residual, and the output of theforward secondary transform of size K2 by (2×K1) is a set of K2coefficients which replace the same two sets of K1 input coefficients.This set of K2 coefficients is entropy-coded separately from the twosets of (N1×N2−K1) coefficients on which the secondary transform is notapplied. The input of the inverse secondary transform of size (2×K1) byK2 is the quantized coefficient vector of size K2 by 1 and the output ofthe inverse secondary transform is a coefficient vector of size (2×K1),from which each K1 coefficients will be concatenated back with each ofthe (N1×N2-K1) coefficients entropy-coded separately. In one embodiment,if the coordinate (x, y) associated with the coefficients meets thecondition that x+y is greater than or equal to a given threshold valueT, then the coefficients are always set as 0. Example values of Tincludes, but not limited to integers between 0 and 32. In oneembodiment, the coefficients which apply both primary and secondarytransform and the coefficient which apply only primary transform arecoded separately. That is, the coefficients which apply both primary andsecondary transform may be coded first, the coefficient which apply onlyprimary transform are coded second, and vice versa.

Although the flow diagram 1500 has been described with respect tochroma, it is also disclosed herein that the flow diagram 1500 mayinclude other embodiments. In one embodiment, the said methods areapplied to the Luma prediction residual with either one of the chromaprediction residuals. In one embodiment, the said methods are appliedbetween a selected two components of any multi-component signals whereapplicable. In one embodiment, any of the methods of S152 and of S152from S156 can be applied for the entire M-component signals byconcatenating the M input blocks. In one embodiment, the methods withrespect to S155 in can be applied for the entire M-component signals byperforming an M-dimensional transform.

That is, there may be a generalization to other types of multi-channelsignal such that a residual from Luma can be correlated to that ofChroma, generic multichannel signals can benefit also, methods of2D-transform, S152, and Secondary-transform, S152 from S156, can beapplied by concatenating the M-input blocks to form the input inM-channel signal cases, and an M-dimensional transform may be applied.

The output 153 may be an output with respect to any one or more ofcoding and decoding by the features described herein and discussedfurther below with respect to FIGS. 17-19.

FIG. 17 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and decoder in astreaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem 1703, that caninclude a video source 1701, for example a digital camera, creating, forexample, an uncompressed video sample stream 1713. That sample stream1713 may be emphasized as a high data volume when compared to encodedvideo bitstreams and can be processed by an encoder 1702 coupled to thecamera 1701. The encoder 1702 can include hardware, software, or acombination thereof to enable or implement aspects of the disclosedsubject matter as described in more detail below. The encoded videobitstream 1704, which may be emphasized as a lower data volume whencompared to the sample stream, can be stored on a streaming server 1705for future use. One or more streaming clients 1712 and 1707 can accessthe streaming server 1705 to retrieve copies 1708 and 1706 of theencoded video bitstream 1704. A client 1712 can include a video decoder1711 which decodes the incoming copy of the encoded video bitstream 1708and creates an outgoing video sample stream 1710 that can be rendered ona display 1709 or other rendering device (not depicted). In somestreaming systems, the video bitstreams 1704, 1706 and 1708 can beencoded according to certain video coding/compression standards.Examples of those standards are noted above and described furtherherein.

FIG. 18 may be a functional block diagram of a video decoder 1800according to an embodiment of the present invention.

A receiver 1802 may receive one or more codec video sequences to bedecoded by the decoder 1800; in the same or another embodiment, onecoded video sequence at a time, where the decoding of each coded videosequence is independent from other coded video sequences. The codedvideo sequence may be received from a channel 1801, which may be ahardware/software link to a storage device which stores the encodedvideo data. The receiver 1802 may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver 1802 may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory 1803 may be coupled inbetween receiver 1802 and entropy decoder/parser 1804 (“parser”henceforth). When receiver 1802 is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosychronous network, the buffer 1803 may not be needed, or can besmall. For use on best effort packet networks such as the Internet, thebuffer 1803 may be required, can be comparatively large and canadvantageously of adaptive size.

The video decoder 1800 may include a parser 1804 to reconstruct symbols1813 from the entropy coded video sequence. Categories of those symbolsinclude information used to manage operation of the decoder 1800, andpotentially information to control a rendering device such as a display1812 that is not an integral part of the decoder but can be coupled toit. The control information for the rendering device(s) may be in theform of Supplementary Enhancement Information (SEI messages) or VideoUsability Information parameter set fragments (not depicted). The parser1804 may parse/entropy-decode the coded video sequence received. Thecoding of the coded video sequence can be in accordance with a videocoding technology or standard, and can follow principles well known to aperson skilled in the art, including variable length coding, Huffmancoding, arithmetic coding with or without context sensitivity, and soforth. The parser 1804 may extract from the coded video sequence, a setof subgroup parameters for at least one of the subgroups of pixels inthe video decoder, based upon at least one parameters corresponding tothe group. Subgroups can include Groups of Pictures (GOPs), pictures,tiles, slices, macroblocks, Coding Units (CUs), blocks, Transform Units(TUs), Prediction Units (PUs) and so forth. The entropy decoder/parsermay also extract from the coded video sequence information such astransform coefficients, quantizer parameter values, motion vectors, andso forth.

The parser 1804 may perform entropy decoding/parsing operation on thevideo sequence received from the buffer 1803, so to create symbols 1813.The parser 1804 may receive encoded data, and selectively decodeparticular symbols 1813. Further, the parser 1804 may determine whetherthe particular symbols 1813 are to be provided to a Motion CompensationPrediction unit 1806, a scaler/inverse transform unit 1805, an IntraPrediction Unit 1807, or a loop filter 1811.

Reconstruction of the symbols 1813 can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser 1804. The flow of such subgroup control information between theparser 1804 and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, decoder 1800 can beconceptually subdivided into a number of functional units as describedbelow. In a practical implementation operating under commercialconstraints, many of these units interact closely with each other andcan, at least partly, be integrated into each other. However, for thepurpose of describing the disclosed subject matter, the conceptualsubdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit 1805. Thescaler/inverse transform unit 1805 receives quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) 1813 from the parser 1804. It can output blockscomprising sample values, that can be input into aggregator 1810.

In some cases, the output samples of the scaler/inverse transform 1805can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit 1807. In some cases, the intra pictureprediction unit 1807 generates a block of the same size and shape of theblock under reconstruction, using surrounding already reconstructedinformation fetched from the current (partly reconstructed) picture1809. The aggregator 1810, in some cases, adds, on a per sample basis,the prediction information the intra prediction unit 1807 has generatedto the output sample information as provided by the scaler/inversetransform unit 1805.

In other cases, the output samples of the scaler/inverse transform unit1805 can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a Motion Compensation Prediction unit 1806 canaccess reference picture memory 1808 to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols 1813 pertaining to the block, these samples can beadded by the aggregator 1810 to the output of the scaler/inversetransform unit (in this case called the residual samples or residualsignal) so to generate output sample information. The addresses withinthe reference picture memory form where the motion compensation unitfetches prediction samples can be controlled by motion vectors,available to the motion compensation unit in the form of symbols 1813that can have, for example X, Y, and reference picture components.Motion compensation also can include interpolation of sample values asfetched from the reference picture memory when sub-sample exact motionvectors are in use, motion vector prediction mechanisms, and so forth.

The output samples of the aggregator 1810 can be subject to various loopfiltering techniques in the loop filter unit 1811. Video compressiontechnologies can include in-loop filter technologies that are controlledby parameters included in the coded video bitstream and made availableto the loop filter unit 1811 as symbols 1813 from the parser 1804, butcan also be responsive to meta-information obtained during the decodingof previous (in decoding order) parts of the coded picture or codedvideo sequence, as well as responsive to previously reconstructed andloop-filtered sample values.

The output of the loop filter unit 1811 can be a sample stream that canbe output to the render device 1812 as well as stored in a referencepicture memory for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. Once a coded picture is fullyreconstructed and the coded picture has been identified as a referencepicture (by, for example, parser 1804), the current reference picture1809 can become part of the reference picture buffer 1808, and a freshcurrent picture memory can be reallocated before commencing thereconstruction of the following coded picture.

The video decoder 1800 may perform decoding operations according to apredetermined video compression technology. The coded video sequence mayconform to a syntax specified by the video compression technology orstandard being used, in the sense that it adheres to the syntax of thevideo compression technology or standard, as specified in the videocompression technology document or standard and specifically in theprofiles document therein. Also necessary for compliance can be that thecomplexity of the coded video sequence is within bounds as defined bythe level of the video compression technology or standard. In somecases, levels restrict the maximum picture size, maximum frame rate,maximum reconstruction sample rate (measured in, for example megasamplesper second), maximum reference picture size, and so on. Limits set bylevels can, in some cases, be further restricted through HypotheticalReference Decoder (HRD) specifications and metadata for HRD buffermanagement signaled in the coded video sequence.

In an embodiment, the receiver 1802 may receive additional (redundant)data with the encoded video. The additional data may be included as partof the coded video sequence(s). The additional data may be used by thevideo decoder 1800 to properly decode the data and/or to more accuratelyreconstruct the original video data. Additional data can be in the formof, for example, temporal, spatial, or signal-to-noise ratio (SNR)enhancement layers, redundant slices, redundant pictures, forward errorcorrection codes, and so on.

FIG. 19 may be a functional block diagram of a video encoder 1900according to an embodiment of the present disclosure.

The encoder 1900 may receive video samples from a video source 1901(that is not part of the encoder) that may capture video image(s) to becoded by the encoder 1900.

The video source 1901 may provide the source video sequence to be codedby the encoder (1703) in the form of a digital video sample stream thatcan be of any suitable bit depth (for example: 8 bit, 10 bit, 12 bit, .. . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ) and anysuitable sampling structure (for example Y CrCb 4:2:0, Y CrCb 4:4:4). Ina media serving system, the video source 1901 may be a storage devicestoring previously prepared video. In a videoconferencing system, thevideo source 1901 may be a camera that captures local image informationas a video sequence. Video data may be provided as a plurality ofindividual pictures that impart motion when viewed in sequence. Thepictures themselves may be organized as a spatial array of pixels,wherein each pixel can comprise one or more samples depending on thesampling structure, color space, etc. in use. A person skilled in theart can readily understand the relationship between pixels and samples.The description below focuses on samples.

According to an embodiment, the encoder 1900 may code and compress thepictures of the source video sequence into a coded video sequence 1910in real time or under any other time constraints as required by theapplication. Enforcing appropriate coding speed is one function ofcontroller 1902. Controller controls other functional units as describedbelow and is functionally coupled to these units. The coupling is notdepicted for clarity. Parameters set by controller can include ratecontrol related parameters (picture skip, quantizer, lambda value ofrate-distortion optimization techniques, . . . ), picture size, group ofpictures (GOP) layout, maximum motion vector search range, and so forth.A person skilled in the art can readily identify other functions ofcontroller 1902 as they may pertain to video encoder 1900 optimized fora certain system design.

Some video encoders operate in what a person skilled in the art readilyrecognizes as a “coding loop.” As an oversimplified description, acoding loop can consist of the encoding part of an encoder 1902 (“sourcecoder” henceforth) (responsible for creating symbols based on an inputpicture to be coded, and a reference picture(s)), and a (local) decoder1906 embedded in the encoder 1900 that reconstructs the symbols tocreate the sample data that a (remote) decoder also would create (as anycompression between symbols and coded video bitstream is lossless in thevideo compression technologies considered in the disclosed subjectmatter). That reconstructed sample stream is input to the referencepicture memory 1905. As the decoding of a symbol stream leads tobit-exact results independent of decoder location (local or remote), thereference picture buffer content is also bit exact between local encoderand remote encoder. In other words, the prediction part of an encoder“sees” as reference picture samples exactly the same sample values as adecoder would “see” when using prediction during decoding. Thisfundamental principle of reference picture synchronicity (and resultingdrift, if synchronicity cannot be maintained, for example because ofchannel errors) is well known to a person skilled in the art.

The operation of the “local” decoder 1906 can be the same as of a“remote” decoder 1800, which has already been described in detail abovein conjunction with FIG. 18. Briefly referring also to FIG. 19, however,as symbols are available and en/decoding of symbols to a coded videosequence by entropy coder 1908 and parser 1904 can be lossless, theentropy decoding parts of decoder 1800, including channel 1801, receiver1802, buffer 1803, and parser 1804 may not be fully implemented in localdecoder 1906.

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. The description of encodertechnologies can be abbreviated as they are the inverse of thecomprehensively described decoder technologies. Only in certain areas amore detail description is required and provided below.

As part of its operation, the source coder 1903 may perform motioncompensated predictive coding, which codes an input frame predictivelywith reference to one or more previously-coded frames from the videosequence that were designated as “reference frames.” In this manner, thecoding engine 1907 codes differences between pixel blocks of an inputframe and pixel blocks of reference frame(s) that may be selected asprediction reference(s) to the input frame.

The local video decoder 1906 may decode coded video data of frames thatmay be designated as reference frames, based on symbols created by thesource coder 1903. Operations of the coding engine 1907 mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 19), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder 1906 replicates decodingprocesses that may be performed by the video decoder on reference framesand may cause reconstructed reference frames to be stored in thereference picture cache 1905. In this manner, the encoder 1900 may storecopies of reconstructed reference frames locally that have commoncontent as the reconstructed reference frames that will be obtained by afar-end video decoder (absent transmission errors).

The predictor 1904 may perform prediction searches for the coding engine1907. That is, for a new frame to be coded, the predictor 404 may searchthe reference picture memory 1905 for sample data (as candidatereference pixel blocks) or certain metadata such as reference picturemotion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor1904 may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor 1904, an input picture may haveprediction references drawn from multiple reference pictures stored inthe reference picture memory 1905.

The controller 1902 may manage coding operations of the video coder1903, including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder 1908. The entropy coder translatesthe symbols as generated by the various functional units into a codedvideo sequence, by loss-less compressing the symbols according totechnologies known to a person skilled in the art as, for exampleHuffman coding, variable length coding, arithmetic coding, and so forth.

The transmitter 1909 may buffer the coded video sequence(s) as createdby the entropy coder 1908 to prepare it for transmission via acommunication channel 1911, which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter1909 may merge coded video data from the video coder 1903 with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller 1902 may manage operation of the encoder 1900. Duringcoding, the controller 1905 may assign to each coded picture a certaincoded picture type, which may affect the coding techniques that may beapplied to the respective picture. For example, pictures often may beassigned as one of the following frame types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other frame in the sequence as a source of prediction.Some video codecs allow for different types of Intra pictures,including, for example Independent Decoder Refresh Pictures. A personskilled in the art is aware of those variants of I pictures and theirrespective applications and features.

A Predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A Bi-directionally Predictive Picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded non-predictively,via spatial prediction or via temporal prediction with reference to onepreviously coded reference pictures. Blocks of B pictures may be codednon-predictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video coder 1900 may perform coding operations according to apredetermined video coding technology or standard. In its operation, thevideo coder 1900 may perform various compression operations, includingpredictive coding operations that exploit temporal and spatialredundancies in the input video sequence. The coded video data,therefore, may conform to a syntax specified by the video codingtechnology or standard being used.

In an embodiment, the transmitter 1909 may transmit additional data withthe encoded video. The source coder 1903 may include such data as partof the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, Supplementary EnhancementInformation (SEI) messages, Visual Usability Information (VUI) parameterset fragments, and so on.

Some embodiments may relate to a system, a method, and/or a computerreadable medium at any possible technical detail level of integration.The computer readable medium may include a computer-readablenon-transitory storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outoperations.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program code/instructions for carrying out operationsmay be assembler instructions, instruction-set-architecture (ISA)instructions, machine instructions, machine dependent instructions,microcode, firmware instructions, state-setting data, configuration datafor integrated circuitry, or either source code or object code writtenin any combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects or operations.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer readable media according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of instructions,which comprises one or more executable instructions for implementing thespecified logical function(s). The method, computer system, and computerreadable medium may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in theFigures. In some alternative implementations, the functions noted in theblocks may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed concurrently orsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwaremay be designed to implement the systems and/or methods based on thedescription herein.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

The descriptions of the various aspects and embodiments have beenpresented for purposes of illustration, but are not intended to beexhaustive or limited to the embodiments disclosed. Even thoughcombinations of features are recited in the claims and/or disclosed inthe specification, these combinations are not intended to limit thedisclosure of possible implementations. In fact, many of these featuresmay be combined in ways not specifically recited in the claims and/ordisclosed in the specification. Although each dependent claim listedbelow may directly depend on only one claim, the disclosure of possibleimplementations includes each dependent claim in combination with everyother claim in the claim set. Many modifications and variations will beapparent to those of ordinary skill in the art without departing fromthe scope of the described embodiments. The terminology used herein waschosen to best explain the principles of the embodiments, the practicalapplication or technical improvement over technologies found in themarketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein.

What is claimed is:
 1. A method of video decoding performed by at leastone processor, the method comprising: receiving video data in an AOMediaVideo 1 (AV1) format comprising data of at least two chromaprediction-residual signal blocks; performing a transformation betweenat least one signal block, having a size less than or equal to acombination of the chroma prediction-residual signal blocks, and thechroma prediction-residual signal blocks; and decoding the video databased on an output of the transformation comprising the at least onesignal block having the size less than or equal to the combination ofthe chroma prediction-residual blocks, wherein the chromaprediction-residual signal blocks comprise an N1×N2 Cb residual blockand an N1×N2 Cr residual block, wherein the at least one signal blockcomprises a 2×N1×N2 three-dimensional (3-D) cubic, wherein thetransformation comprises a two-point 1-D transform, on each of 2×1vectors along a z-axis of the 3-D cubic, and an N1×N2 transform on anx-y plane of the 3-D cubic.
 2. The method according to claim 1, whereinthe transformation further comprises dequantizing signaled indices ofcoefficients of the at least one signal block, having the size less thanor equal to the combination of the chroma prediction-residual signalblocks, and transforming the dequantized signaled indices by a 2×N1×N2by L×M matrix, wherein 2×N1×N2 is a size of the combination of thechroma prediction-residual blocks, and wherein L×M is the size less thanor equal to the combination of the chroma prediction residual blocs. 3.The method according to claim 2, wherein a result of transforming thedequantized signaled indices by a 2×N1×N2 by L×M matrix comprises areconstructed 2×N1×N2 vector, and wherein decoding the video datacomprises reconstructing the N1×N2 Cb residual block and the N1×N2 Crresidual block from the reconstructed 2×N1×N2 vector.
 4. The methodaccording to claim 3, wherein the at least one signal block comprises aninterleaving of the at least two chroma prediction-residual signalblocks.
 5. The method according to claim 1, wherein the transformationcomprises an N1-point 1-D transform, on each of N1×1 vectors along anx-axis of the 3-D cubic, an N2-point 1-D transform, on each of N2×1vectors along a y-axis of the 3-D cubic, and a 2-point transform on eachof 2×1 vectors along a z-axis of the 3-D cubic.
 6. The method accordingto claim 1, wherein performing the transformation comprises performing aprimary transformation and a secondary transformation.
 7. The methodaccording to claim 6, wherein at least one of the primary transformationand the secondary transformation comprises setting coefficients to zeroin response to determining a predetermined condition in which a value ofa coordinate associated with a coefficient of at least one of the chromaprediction-residual signal blocks is greater than or equal to athreshold value.
 8. An apparatus for video decoding, the apparatuscomprising: at least one memory configured to store computer programcode; at least one processor configured to access the computer programcode and operate as instructed by the computer program code, thecomputer program code including: receiving code configured to cause theat least one processor to receive video data in an AOMedia Video 1 (AV1)format comprising data of at least two chroma prediction-residual signalblocks; performing code configured to cause the at least one processorto perform a transformation between at least one signal block, having asize less than or equal to a combination of the chromaprediction-residual signal blocks, and the chroma prediction-residualsignal blocks; and decoding code configured to cause the at least oneprocessor to decode the video data based on an output of thetransformation comprising the at least one signal block having the sizeless than or equal to the combination of the chroma prediction-residualblocks, wherein the chroma prediction-residual signal blocks comprise anN1×N2 Cb residual block and an N1×N2 Cr residual block, wherein the atleast one signal block comprises a 2×N1×N2 three-dimensional (3-D)cubic, wherein the transformation comprises a two-point 1-D transform,on each of 2×1 vectors along a z-axis of the 3-D cubic, and an N1×N2transform on an x-y plane of the 3-D cubic.
 9. The apparatus accordingto claim 8, wherein the transformation comprises dequantizing signaledindices of coefficients of the at least one signal block, having thesize less than or equal to the combination of the chromaprediction-residual signal blocks, and transforming the dequantizedsignaled indices by a 2×N1×N2 by L×M matrix, wherein 2×N1×N2 is a sizeof the combination of the chroma prediction-residual blocks, and whereinL×M is the size less than or equal to the combination of the chromaprediction residual blocs.
 10. The apparatus according to claim 9,wherein a result of transforming the dequantized signaled indices by a2×N1×N2 by L×M matrix comprises a reconstructed 2×N1×N2 vector, andwherein decoding the video data comprises reconstructing the N1×N2 Cbresidual block and the N1×N2 Cr residual block from the reconstructed2×N1×N2 vector.
 11. The apparatus according to claim 10, wherein the atleast one signal block comprises an interleaving of the at least twochroma prediction-residual signal blocks.
 12. The apparatus according toclaim 8, wherein the transformation comprises an N1-point 1-D transform,on each of N1×1 vectors along an x-axis of the 3-D cubic, an N2-point1-D transform, on each of N2×1 vectors along a y-axis of the 3-D cubic,and a 2-point transform on each of 2×1 vectors along a z-axis of the 3-Dcubic.
 13. The apparatus according to claim 8, wherein performing thetransformation comprises performing a primary transformation and asecondary transformation.
 14. A non-transitory computer readable mediumstoring a program causing a computer to execute a process, the processcomprising: receiving video data in an AOMedia Video 1 (AV1) formatcomprising data of at least two chroma prediction-residual signalblocks; performing a transformation between at least one signal block,having a size less than or equal to a combination of the chromaprediction-residual signal blocks, and the chroma prediction-residualsignal blocks; and decoding the video data based on an output of thetransformation comprising the at least one signal block having the sizeless than or equal to the combination of the chroma prediction-residualblocks, wherein the chroma prediction-residual signal blocks comprise anN1×N2 Cb residual block and an N1×N2 Cr residual block, wherein the atleast one signal block comprises a 2×N1×N2 three-dimensional (3-D)cubic, wherein the transformation comprises a two-point 1-D transform,on each of 2×1 vectors along a z-axis of the 3-D cubic, and an N1×N2transform on an x-y plane of the 3-D cubic.